Perception of electrical and mechanical stimulation of the skin: implications for electrotactile feedback.

Patrick L. Marcus, Andrew J. Fuglevand

Research output: Contribution to journalArticlepeer-review

19 Scopus citations


Spinal cord injury is often accompanied by impaired tactile and proprioceptive sensations. Normally, somatosensensory information derived from such sensations is important in the formation of voluntary motor commands. Therefore, as a preliminary step toward the development of an electrotactile feedback system to restore somatosensation, psychophysical methods were used to characterize perceptual attributes associated with electrical stimulation of the skin on the back of the neck in human subjects. These data were compared to mechanical stimulation of the skin on the back of neck and on the distal pad of the index finger. Spatial acuity of the neck, evaluated using two-point thresholds, was not significantly different for electrical (37 +/- 14 mm) or mechanical stimulation (39 +/- 10 mm). The exponent (beta) of the best fitting power function relating perceived intensity to applied stimulus strength was used to characterize perceptual sensitivity to mechanical and electrical stimuli. For electrical stimuli, both current amplitude-modulated and frequency-modulated trains of pulses were tested. Perceptual sensitivity was significantly greater for current amplitude modulation (beta = 1.14 +/- 0.37) compared to frequency modulation (beta = 0.57 +/- 0.24) and mechanical stimulation (0.51 +/- 0.12). Finally, based on the data gathered here, we derive a transfer function that could be used in the future to convert mechanical stimuli detected with artificial sensors placed on the fingers into electrotactile signals that evoke perceptions similar to those arising from normal mechanical stimulation of the skin.

Original languageEnglish (US)
Pages (from-to)66008
Number of pages1
JournalJournal of neural engineering
Issue number6
StatePublished - Dec 2009

ASJC Scopus subject areas

  • Biomedical Engineering
  • Cellular and Molecular Neuroscience


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